Hands-On Data Structures and Algorithms with Python – Third Edition: Store, manipulate, and access data effectively and boost the performance of your applications , Third Edition

Dr. Basant Agarwal

$49.99

4.8 (26 Ratings)

Paperback Jul 2022 496 pages 3rd Edition

Dr. Basant Agarwal

$49.99

4.8 (26 Ratings)

Paperback Jul 2022 496 pages 3rd Edition

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Hands-On Data Structures and Algorithms with Python – Third Edition

Introduction to Algorithm Design

The objective of this chapter is to understand the principles of designing algorithms, and the importance of analyzing algorithms in solving real-world problems. Given input data, an algorithm is a step-by-step set of instructions that should be executed in sequence to solve a given problem.

In this chapter, we will also learn how to compare different algorithms and determine the best algorithm for the given use-case. There can be many possible correct solutions for a given problem, for example, we can have several algorithms for the problem of sorting n numeric values. So, there is no one algorithm to solve any real-world problem.

In this chapter, we will look at the following topics:

Introducing algorithms
Performance analysis of an algorithm
Asymptotic notation
Amortized analysis
Choosing complexity classes
Computing the running time complexity of an algorithm

Computing the running time complexity of an algorithm

To analyze an algorithm with respect to the best-, worst-, and average-case runtime of the algorithm, it is not always possible to compute these for every given function or algorithm. However, it is always important to know the upper-bound worst-case runtime complexity of an algorithm in practical situations; therefore, we focus on computing the upper-bound Big O notation to compute the worst-case runtime complexity of an algorithm:

Find the worst-case runtime complexity of the following Python snippet:
```
# loop will run n times
for i in range(n):
    print("data")  #constant time
```
Solution: The runtime for a loop, in general, takes the time taken by all statements in the loop, multiplied by the number of iterations. Here, total runtime is defined as follows:

T(n) = constant time (c) * n = c*n = O(n)

Find the time complexity of the following Python snippet: ...

Exercises

Find the time complexity of the following Python snippets:

i=1
while(i<n):
    i*=2
    print("data")

i =n
while(i>0):
    print('complexity')
    i/ = 2

for i in range(1,n):
    j = i
    while(j<n):
        j*=2

i=1
while(i<n):
    print('python')
        i = i**2

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Key benefits

Explore functional and reactive implementations of traditional and advanced data structures
Apply a diverse range of algorithms in your Python code
Implement the skills you have learned to maximize the performance of your applications

Description

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.

Who is this book for?

This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.

What you will learn

Understand common data structures and algorithms using examples, diagrams, and exercises
Explore how more complex structures, such as priority queues and heaps, can benefit your code
Implement searching, sorting, and selection algorithms on number and string sequences
Become confident with key string-matching algorithms
Understand algorithmic paradigms and apply dynamic programming techniques
Use asymptotic notation to analyze algorithm performance with regard to time and space complexities
Write powerful, robust code using the latest features of Python

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MLEngineer Jan 10, 2023

This book strikes the ideal balance between mathematical algorithm theory and coding. There are many-a-book with only theory and a lot of coding sources with very little in terms of explanation/theory.This is a very good book that mixes both. I myself invent/develop algorithms and appreciate very much this book's balanced approach.

Amazon Verified review

v Oct 18, 2022

Most data structure and algorithm book/video have been written/taught using C/C++ or Java in the market. For many python only beginner, epecially in data science/machine leanring, a python version data structure and algorithm book can be a great reference to study high quality programming systemetically, This book fills the gap of the demand. Good job!

Siddhant Kochrekar Apr 23, 2023

While writing production level code, I have encountered many situations where the efficiency of the chosen data structure or algorithm has a significant impact on the performance of the system. I was particularly interested in reviewing this book, as it aims to provide an introduction to the essential topics and extend into practical applications for each of them.It focuses both on theoretical concepts and the practical applications. The simple examples shown in the book are suitable for beginners and the complex problems are framed in such a way that even the experienced developers would benefit. This book assumes a basic level of knowledge in Python programming. In particular, the book could have included generators, decorators, and meta-classes, to showcase how these concepts can be used to implement more efficient data structures and algorithms.The book does provide valuable insights into various data structures and algorithms. The author's explanations of the concepts are clear and concise, and the code examples are well-structured and easy to understand. The book covers a wide range of topics, including linked lists, trees, graphs, and sorting algorithms, making it a comprehensive resource for beginners. Overall it is a useful starting point for beginners who are new to data structures and algorithms and want to use Python as the programming language.

David M. Mar 19, 2023

In this book, the author presented the concept of complex data structures and algorithms in a systematic way with clean examples that can be read and understood by readers and learners having various backgrounds, as for example CS, IT, Business or other quantitative and analytical fields. This book will be useful not only for developers, but also data scientists and data engineers as well.

Agni Oct 18, 2022

The Author demonstrates a fresh look at the subject!I have instructed the course at the University for some time and I loved reading it. I think there are many similar books, but none go to the depths and clarity that this one does. Especially, I liked that fact that the author actually demonstrates all the concepts with examples, and also puts it in tabular format for easy reference.This will be a great asset to have, both for the beginner and for the advanced learner.Enjoy learning!

Hands-On Data Structures and Algorithms with Python – Third Edition: Store, manipulate, and access data effectively and boost the performance of your applications , Third Edition

What do you get with Print?

Hands-On Data Structures and Algorithms with Python – Third Edition

Introduction to Algorithm Design

Introducing algorithms

Performance analysis of an algorithm

Time complexity

Asymptotic notation

Amortized analysis

Composing complexity classes

Computing the running time complexity of an algorithm

Summary

Exercises

Join our community on Discord

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